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Human-machine symbiosis for data interpretation

Much work on search, retrieval and interpretation is caught between the Scylla of restrictive taxonomies and the Charybdis of the semantic web. Too much of IT practice is based on the assumption that the human brain is a "limited capacity information processing device" (A-Level psychology text book) and that language has a common structure and meaning.

In this presentation David Snowden will report on pioneering work on the use of semi-constrained signifier sets, allowing humans to tell and index their own material within a loose structure. This work enables the pattern basis of human intelligence to be augmented by information processing power, without losing the insights that are essentially human in nature. The development is based on more than a decade of work in weak signal detection and on overcoming cognitive bias in intelligence and decision support systems. Results will be presented at the seminar.